A Cognitive Theory of Reasoning and Choice

Bordalo, Gennaioli, Lanzani, and Shleifer develop a cognitive theory of choice in which a decision maker’s attention to the features of options is determined by her categorization of the current problem against a memory database of problems she solved in the past. The core claim is that before solving a problem, the decision maker asks “what kind of problem is this?” and resolves it by selecting the category — indexed by a prototype attention-plus-context vector and a time-discounted frequency — whose similarity to the current problem is maximized. This problem recognition step then pins down which features (price, quality, probabilities) receive attention, which in turn shapes valuation and choice.

Dynamic Concern for Misspecification

Research Question

This paper asks how an agent who fears that none of their probabilistic models is the correct description of the data-generating process (DGP) should update that fear as evidence accumulates, and what long-run behavior such an agent exhibits. The central contribution is making the concern for misspecification endogenous: the better the agent’s structured models explain past observations, the less concerned the agent becomes.

Decision Criterion

The agent posits a finite-dimensional parametric set of structured models Θ, holds a prior µ over Θ, and evaluates each action according to an average robust control criterion. This criterion takes a weighted average (over models) of robust control assessments, where each assessment penalizes expected utility for probability distributions that deviate from the structured model in terms of relative entropy, scaled by a misspecification concern parameter λ > 0. A standard subjective expected utility maximizer is the limiting case as λ → 0 (no concern), and a maxmin agent is approached as λ → ∞.

Giacomo Lanzani | Macro Paper Warehouse

A Cognitive Theory of Reasoning and Choice

Dynamic Concern for Misspecification